Build a data ingestion pipeline using Kafka, Flink, and CrateDB

1

Apache Flink

Kafka is the front line of the stack, used to queue messages received from (for example) IoT sensors and devices. CrateDB will query and store the data. And between CrateDB and Kafka, it lives Apache Flink, a data processing engine. These three tools are all distributed systems that provide elastic scaling, fault tolerance, high-throughput, and low-latency performance via parallel processing.

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2

CrateDB

Kafka is the front line of the stack, used to queue messages received from (for example) IoT sensors and devices. CrateDB will query and store the data. And between CrateDB and Kafka, it lives Apache Flink, a data processing engine. These three tools are all distributed systems that provide elastic scaling, fault tolerance, high-throughput, and low-latency performance via parallel processing.

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3

Homebrew

This guide assumes you have Docker, Git, Homebrew, and Wget installed. If you don't have/don't want to install these components in your machine, you can always use alternatives, but the steps on this guide will follow more smoothly if you have them installed.

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